Electioneering: Part III

Last time we determined the makeup of parliament under the three different systems. This time, we’ll reframe these results so we can perform a side-to-side analysis and draw some reasonable inferences. If you’ve skipped to the end¹, a reminder that the series is divided into three parts:

¹ This is the good bit, though.

• Part One
  Will define the question, provide some overview of the different electoral systems, and clean the data.
• Part Two
  Conduct the analysis, and generate some preliminary results.
• Part Three
  Refine the analysis, and offer some interpetation.

Due to the presence of list seats in an MMP system, looking at electorates alone elides the comparative advantage of the MMP system. For this reason, I’ve broken this section into two subsections: the first determines the total composition of parliament under each of FPTP, MMP, and STV, whilst the second compares the winners of electorates under FFP and STV.

Composition by Party

compare.parliament = votes %>%
  group_by(PartyAb) %>%
  filter(CountNumber == 0) %>%
  summarise(partyVoteN = sum(prefCount)) %>%
  mutate(partyVotePC = (partyVoteN / sum(partyVoteN)) %>%
           multiply_by(100) %>%
           round(digits = 2)) %>%
  # Join to MMP
  full_join(mmp %>%
              select(PartyAb,
                     mmpElecSeatsN = seatsElecN,
                     mmpListSeatsN = seatsListN,
                     mmpTotSeatsN = seatsTotalN,
                     mmpTotSeatsPC = seatsTotalPC)) %>%
  # Join to STV
  full_join(stv %>%
              group_by(PartyAb) %>%
              summarise(stvSeatsN = n())) %>%
  # Join to FPTP
  full_join(fptp %>%
              group_by(PartyAb) %>%
              summarise(fptpSeatsN = n())) %>%
  # Tidy up the missing
  mutate(across(c(stvSeatsN, fptpSeatsN), ~ ifelse(is.na(.), 0, .)),
         stvSeatsPC = (stvSeatsN / sum(stvSeatsN)) %>%
                  multiply_by(100) %>%
                  round(digits = 2),
         fptpSeatsPC = (fptpSeatsN / sum(fptpSeatsN)) %>%
           multiply_by(100) %>%
           round(digits = 2)) %>%
  # Difference from party vote
  mutate(across(ends_with("SeatsPC"), ~ . - partyVotePC, .names = "{.col}_diff"))

Comparison of Parliament Under Three Voting Systems
Australian Federal Election 2022
Party	Party Vote (%)	Mixed Member Proportional			Single Transferrable Vote			First Past the Post
		Seats (n)	Seats (%)	Deviance (%)	Seats (n)	Seats (%)	Deviance (%)	Seats (n)	Seats (%)	Deviance (%)
ALP	32.58	81	36.65	4.07	77	50.99	18.41	71	47.02	14.44
LP	23.89	59	26.70	2.81	27	17.88	-6.01	40	26.49	2.60
GRN	12.25	31	14.03	1.78	4	2.65	-9.60	2	1.32	-10.93
LNP	8.00	23	10.41	2.41	21	13.91	5.91	23	15.23	7.23
IND	5.30	3	1.36	-3.94	10	6.62	1.32	3	1.99	-3.31
ON	4.96	12	5.43	0.47	0	0.00	-4.96	0	0.00	-4.96
UAPP	4.12	0	0.00	-4.12	0	0.00	-4.12	0	0.00	-4.12
NP	3.60	10	4.52	0.92	10	6.62	3.02	10	6.62	3.02
LDP	1.73	0	0.00	-1.73	0	0.00	-1.73	0	0.00	-1.73
AJP	0.60	0	0.00	-0.60	0	0.00	-0.60	0	0.00	-0.60
CYA	0.39	0	0.00	-0.39	0	0.00	-0.39	0	0.00	-0.39
KAP	0.38	1	0.45	0.07	1	0.66	0.28	1	0.66	0.28
XEN	0.25	1	0.45	0.20	1	0.66	0.41	1	0.66	0.41
WAP	0.23	0	0.00	-0.23	0	0.00	-0.23	0	0.00	-0.23
GAP	0.21	0	0.00	-0.21	0	0.00	-0.21	0	0.00	-0.21
Deviance is the percentage difference between the proportion of seats held compared to the 1st preference vote.
NB: Parties receiving fewer than 30,000 votes are not displayed.

Composition by Electorates

compare.seat = full_join(
  stv %>%
    mutate(name = paste(GivenNm, Surname)) %>%
    select(StateAb, DivisionNm,
           stvID = CandidateID, stvName = name, stvParty = PartyAb, stvCount = prefCount, stvMargin = margin),
  fptp %>%
    mutate(name = paste(GivenNm, Surname)) %>%
    select(StateAb, DivisionNm,
           fptpID = CandidateID, fptpName = name, fptpParty = PartyAb, fptpCount = prefCount, fptpMargin = margin),
  by = c("StateAb", "DivisionNm")) %>%
  mutate(identical = ifelse(stvID == fptpID, TRUE, FALSE)) %>%
  select(-c(stvID, fptpID))

Comparison of Electorates with Differing Outcomes Under STV and FPTP
Australian Federal Election 2022
	State	Single Transferable Vote				First Past the Post
		Elected Member	Party	Votes (n)	Margin (n)	Elected Member	Party	Votes (n)	Margin (n)
Bennelong	NSW	Jerome LAXALE	ALP	50,801.00	1,954.00	Simon KENNEDY	LP	41,206.00	3,610.00
Boothby	SA	Louise MILLER-FROST	ALP	60,579.00	7,451.00	Rachel SWIFT	LP	43,196.00	6,450.00
Brisbane	QLD	Stephen BATES	GRN	58,460.00	8,122.00	Trevor EVANS	LNP	41,032.00	11,380.00
Curtin	WA	Kate CHANEY	IND	53,847.00	2,657.00	Celia HAMMOND	LP	43,408.00	12,466.00
Fowler	NSW	Dai LE	IND	44,348.00	2,793.00	Kristina KENEALLY	ALP	30,973.00	5,627.00
Gilmore	NSW	Fiona PHILLIPS	ALP	56,039.00	373.00	Andrew CONSTANCE	LP	46,941.00	6,766.00
Goldstein	VIC	Zoe DANIEL	IND	51,861.00	5,635.00	Tim WILSON	LP	39,607.00	5,792.00
Higgins	VIC	Michelle ANANDA-RAJAH	ALP	49,726.00	3,941.00	Katie ALLEN	LP	38,859.00	11,672.00
Kooyong	VIC	Monique RYAN	IND	54,276.00	6,035.00	Josh FRYDENBERG	LP	43,736.00	2,433.00
Lyons	TAS	Brian MITCHELL	ALP	37,341.00	1,344.00	Susie BOWER	LP	27,296.00	6,001.00
Mackellar	NSW	Sophie SCAMPS	IND	51,973.00	4,955.00	Jason FALINSKI	LP	40,993.00	3,269.00
North Sydney	NSW	Kylea Jane TINK	IND	51,392.00	5,666.00	Trent ZIMMERMAN	LP	36,956.00	12,479.00
Robertson	NSW	Gordon REID	ALP	50,277.00	4,344.00	Lucy WICKS	LP	38,448.00	2,217.00
Ryan	QLD	Elizabeth WATSON-BROWN	GRN	52,286.00	5,256.00	Julian SIMMONDS	LNP	38,239.00	8,236.00
Tangney	WA	Sam LIM	ALP	56,331.00	5,114.00	Ben MORTON	LP	43,008.00	2,068.00
Wentworth	NSW	Allegra SPENDER	IND	48,186.00	7,449.00	Dave SHARMA	LP	35,995.00	4,185.00

Electoral Maps

First Past the Post

Single Transferable Vote